Question 21
Content Domain 3: ModelingA binary classification model is evaluated with a confusion matrix. Which quantity represents the number of actual positive cases that the model incorrectly predicted as negative?
Correct answer: C
Explanation
In a confusion matrix, false negatives are actual positive cases that the model predicts as negative, while false positives are actual negative cases predicted as positive. — Confusion matrix terminology
Why each option is right or wrong
A. True positives
True positives are actual positive cases predicted as positive.
B. False positives
False positives are actual negative cases predicted as positive.
C. False negatives
In confusion matrix terminology, a false negative occurs when the actual class is positive but the model prediction is negative, matching the question exactly.
D. True negatives
True negatives are actual negative cases predicted as negative.